Statistics › Section J · Hypothesis testing with two samples › Topic J.2
Effect sizes and reading tests responsibly
"p < 0.05" is where the public story starts and the statistician's questions begin. Is the effect large enough to matter? Was the design honest? Would it replicate? This topic builds the habits that separate reading a significant result from trusting one.
In this topic
- Beyond the threshold
- Effect sizes
- Cohen's d
- Worked example: the tutoring effect, sized
- Significance is not importance
- Thresholds are conventions
- Intervals and tests agree
- The replication crisis
- Worked example: reading a news claim
- A Bayesian footnote
- Common mistakes to avoid
- Key takeaways
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